Before a company rolls AI out to everyone, the people running it need to know what it is for, how they will use it, and what the rest of the company should expect.
Most enterprise AI rollouts follow the same order. The company buys licenses, IT sets up access, HR schedules training, and an announcement goes out telling everyone the tools are available. A few months later, usage is uneven and nobody can say what changed in the business.
When I look at where those rollouts stall, the problem usually sits at the top of the org chart. The leadership team approved the spend, but it never decided what AI should do for the business, and most of the executives are not using it in their own work. The rest of the company notices.
That is why our enablement work starts with the executive team before anything goes company-wide.
What employees are seeing.
Gallup's tracking shows the gap clearly. As of May 2026, only 25% of U.S. employees say their organization has communicated a clear plan for integrating AI into its work (Gallup). In a February 2026 study of more than 23,000 employees, Gallup found that in organizations using AI, 78% of employees whose manager actively supports AI are frequent users. Among employees who do not strongly agree their manager supports it, that figure is 44% (Gallup).
The view from the top looks different. In Wharton's 2025 survey of 800 senior leaders at large U.S. companies, 56% of leaders at the vice president level and above said their organization was adopting AI much faster than others. Only 28% of managers said the same (Wharton Human-AI Research).
Leaders believe the rollout is going well. The people doing the work are waiting for direction. A company-wide deployment widens that gap when the leadership team has not done its part first.
Leaders decide what AI is for.
Every company that deploys AI has to answer questions only the leadership team can answer. Which work should AI take on? Which decisions stay with people? What does good output look like in finance, in sales, in operations? Where will the savings or added capacity show up on the P&L?
If those answers do not exist before rollout, every team makes up its own. Some build useful workflows. Most go back to drafting emails and summarizing meetings, because nobody told them what else mattered.
Leaders set the rules.
AI changes where information goes. Board materials, pricing, customer data, employee records and deal terms all end up in front of a model at some point. The executive team needs to decide what can be shared, with which tools, and who is accountable when something goes wrong.
Those decisions are much harder to make after hundreds of employees have already formed habits.
Leaders have to use it.
Teams copy what their leaders do. When the CEO walks into the weekly meeting with an AI-prepared brief and the CFO uses it to build the forecast review, people see that AI is part of how the company runs. When the leadership team keeps it at arm's length, employees read that too.
Gallup's research names manager support as the strongest driver of AI use (Gallup). Managers take their cues from the executives above them.
Leadership work is the real test.
Executive work is some of the most complex and highest-stakes work in a company: board preparation, forecasting, hiring decisions and strategy calls made with incomplete information. When AI handles part of that work well, leaders see its value firsthand and can explain it with conviction. They also learn its limits, which makes them better at setting expectations for everyone else.
What executive enablement looks like.
Our Executive AI Operating System engagement is built for the CEO and the leadership team. It starts with role and decision mapping. That covers who decides what, what each leader needs in front of them, and which recurring work takes the most time. From there we build custom AI systems around how each leader runs their part of the business, using the company's own context, examples and standards.
Every executive completes the foundational training before the first live session, so our time together goes to their real work. By the end, the leadership team has its own working systems, a shared set of rules for AI use, and a plan for how AI rolls out to the rest of the company.
Five questions to answer before going company-wide.
- Can the leadership team say in one sentence what AI is supposed to do for the business this year?
- Has each executive used AI in their own recurring work for at least a month?
- Is there a written decision on what information can and cannot go into AI tools?
- Does every function head know which of their team's workflows should change first?
- Is there a way to measure whether the business changed, beyond counting logins?
If the answer to most of these is no, the rollout will likely repeat the pattern above. Starting with the leadership team takes a few months. It gives everything that follows a clear direction and a group of leaders who can show the rest of the company how it is done.
If you are planning an enterprise AI rollout and want to start with your leadership team, request a strategy session.
Before AI goes to everyone, it has to work for the people running the company.
